Dear list,

I'm  working with microarray expression data and I am using limma to detect
differentially expressed genes. I have some questions about the design
matrix and the handling of biological and technical replicates.

The target file is:

Sample_name                 sample_type                     sample_replicate
disease_status

MPM_07                                            1
1                                             1

MPM_08                                            1
2                                             1

MPM_09                                            1
3                                             1

MPM_10_a                                       1
4                                             1

MPM_10_b                                       1
4                                             1

MPM_11                                            1
5                                             1

MPM_12                                            1
6                                             1

PP_01_a                                             2
7                                             0

PP_01_b                                             2
7                                             0

PP_02                                                  2
8                                             0

PP_03                                                  2
9                                             0

PP_04                                                  2
10                                          0

PP_05                                                  2
11                                          0

PP_06                                                  2
12                                          0

PV_02                                                  3
13                                          0

PV_03                                                  3
14                                          0

PV_04                                                  3
15                                          0

PV_05                                                  3
16                                          0

Each sample is hybridized on an Affymetrix HG-U133-Plus2 array.

So I have 7 mesothelioma samples (sample_type=1) where 2 were from the same
patient (MPM_10 a e b)), 7 parietal pleural samples (sample_type= 2) where 2
were from the same patient (PP_01 a e b) and 4 visceral pleural samples
(sample_type= 3). In reality 4 parietal pleural samples (PP_02,PP_03,PP_04
and PP_05) and 4 visceral pleural samples (PV_02,PV_03,PV_04 and PV_05) come
from the same patients.

pd <- data.frame(sample_type= c(rep(1,7),rep(2,7),rep(3,4)),
sample_replicate = c(1:4,4,5,6,7,7,8:12,13:16),
disease_status=c(rep(1,7),rep(0,11)))

biolrep<-pd$sample_replicate

f<- factor(pd$sample_type)

design<- model.matrix(~0+f)

colnames(design)<- c("MPM", "PP", "PV")

I tried to handle technical replicates using the block argument of function
duplicatecorrelation() as follows:

corfit<- duplicateCorrelation(eset_norm_genes_ff_filtered, design, ndups=1,
block= biolrep) # eset_norm_genes_ff_filtered is an ExpressionSet object
containing pre-processed and filtered data

I am interested in identifying differentially expressed genes between MPM
and PP and between PV and PP.

contrast.matrix_all.contrasts<-
makeContrasts(MPMvsPP=MPM-PP,PVvsPP=PV-PP,levels=design)

fit_ff<-lmFit(eset_norm_genes_ff_filtered, design,block=biolrep,
ndups=1,cor=corfit$consensus)

fit2_ff<- contrasts.fit(fit_ff, contrast.matrix_all.contrasts)

fit2e_ff<-eBayes(fit2_ff)

I think that my approach is correct for the first contrast (MPM vs PP) but
not for the second one because biolrep doesn't consider the fact that some
samples between PP and PV are paired.

Am I correct?

What about defining biolrep<-c(1:4,4,5,6,7,7,8:12,8:11)?

Is there a method to handle such an experimental design? 

Sorry for my long post!

Any suggestion/comment is welcome.

Cheers,

Manuela

 

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Manuela Di Russo, Ph.D. Student
Department of Experimental Pathology, MBIE
University of Pisa
Pisa, Italy
e-mail:  <mailto:manuela.dirusso@for.unipi.it> manuela.dirusso@for.unipi.it
mobile: +393208778864

phone: +39050993538

 


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